Contact centers are employed by many enterprises to service inbound and outbound contacts from customers. A typical contact center includes a switch and/or server to receive and route incoming packet-switched and/or circuit-switched contacts and one or more resources, such as human agents and automated resources (e.g., Interactive Voice Response (IVR) units), to service the incoming contacts. Contact centers distribute contacts, whether inbound or outbound, for servicing to any suitable resource according to predefined criteria. In many existing systems, the criteria for servicing the contact from the moment that the contact center becomes aware of the contact until the contact is connected to an agent are client or operator-specifiable (i.e., programmable by the operator of the contact center), via a capability called vectoring. Normally in present-day ACDs when the ACD system's controller detects that an agent has become available to handle a contact, the controller identifies all predefined contact-handling queues for the agent (usually in some order of priority) and delivers to the agent the highest-priority, oldest contact that matches the agent's highest-priority queue. Generally, the only condition that results in a contact not being delivered to an available agent is that there are no contacts waiting to be handled.
The primary objective of contact center management is to ultimately maximize contact center performance and profitability. An ongoing challenge in contact center administration is monitoring and optimizing contact center efficiency. Contact center efficiency is generally measured in two ways.
Service level is one measurement of contact center efficiency. Service level is typically determined by dividing the number of contacts accepted within the specified period by the number accepted plus the number that were not accepted, but completed in some other way (e.g., abandoned, given busy, canceled, flowed out). Of course, service level definitions may vary from one enterprise to another.
Match rate is another indicator used in measuring contact center efficiency. Match rate is usually determined by dividing the number of contacts accepted by a primary skill level agent within a period of time by the number of contacts accepted by any agent for a queue over the same period. An agent with a primary skill level is one that typically can handle contacts of a certain nature most effectively and/or efficiently. There are other contact center agents that may not be as proficient as the primary skill level agent, and those agents are identified either as secondary skill level agents or backup skill level agents. As can be appreciated, contacts received by a primary skill level agent are typically handled more quickly and accurately or effectively (e.g., higher revenue attained) than a contact received by a secondary or even backup skill level agent. Thus, it is an objective of most contact centers to optimize match rate along with service level.
In addition to service level and match rate performance measures, contact centers use other Key Performance Indicators (“KPIs”), such as revenue, estimated, actual, or predicted wait time, average speed of answer, and the like, to calculate performance relative to their Service Level Agreements (“SLAs”). Operational efficiency is achieved when KPIs are managed near, but not above, SLA levels. Many contact centers use administered thresholds to report and track KPI and SLA performance.
Threshold management is a complex task. In the simplest of cases, exceeding a given KPI threshold (i.e., revenue) indicates overperformance and is considered positive for the enterprise. In other cases, exceeding a KPI threshold (i.e., estimated, actual, or predicted wait time) indicates underperformance. When the SLA is not met, there is a negative end result for the enterprise and a monetary penalty may apply. Additionally, overperformance of some KPIs (i.e., average speed of answer) are considered inefficient for the enterprise because they indicate excess resource cost. Ideally, contact centers would like to maximize operating efficiency by operating at or near a given KPI with little deviation.
Currently, Avaya IQ™ and CMS™ by Avaya, Inc., can track KPIs historically relative to a selected threshold. Each time a report refreshes with new data, the updated KPI value is shown. If the KPI is close to a threshold, the report can provide a visual or audible alarm to the operator. When a threshold is crossed, the operator is left to his or her own devices to determine what needs to be done. Management systems cannot predict if and when the threshold would be met or exceeded let alone understand the penalties for failing to meet a threshold. Forward thinking contact centers often try to optimize operations in real time using thresholds. This requires the contact center personnel to calculate the probability of meeting or exceeding the threshold, the potential consequences, the best course of action, and the response time. These are complex and potentially error prone calculations that are made on the fly by contact center staff.
There is thus a need for a contact center that can monitor performance relative to one or more selected KPIs.